**9.1 Application of ADM1 model for simulation of organic solid waste**

Concerning simulations of TCOD and SCOD, and TVFA, after estimation of substrate disintegration and hydrolysis parameters, it can be noticed that the simulated results are in good agreement with the experimental ones as shown on figure 7 and 8 respectively.



Table 2. Influent characteristics

164 Biogas

Since its development in 2002 and up to now, the ADM1 has been tested and used on different substrates where a great number of research works are reported in the literature. As examples, one can cite (Blumensaat and Keller, 2005) who modified the initial version of ADM1 for the simulation of a dynamic behaviour of a pilot scale digester using sludge, in order to ensure a faultless model implementation. They obtained accurate results for the cases of low to medium loading rates. However the accuracy showed a decline with the

Wayne and Parker, 2005) considered the application of the ADM1 to a variety of anaerobic digestion configurations where the results showed, in most of the considered cases, that the

(Feng et al., 2006) found that the ADM1 is not sensitive to the distribution ratio of carbohydrates, proteins and lipids, whereas the fraction of short chain fatty acids (SCFA) in

Consequently, the great capabilities of ADM1 in modelling different types of substrates and calculations have been the motivating factor to use it in the present work to evaluate the performances of a co-digestion process for the treatment of organic municipal solid waste and waste activated sludge in the above mentioned 2000 m3 reactor working at a

As mentioned above the ADM1 (Anaerobic Digestion Model No. 1) was developed by the IWA group (Batstone et al., 2002) with the objective to build a full mathematical model based intimately on the phenomenological model in order to simulate, at best, anaerobic reactors. It includes, as a first step, the disintegration of solid complexes (non biological step) into carbohydrates, lipids, proteins and inert material (soluble and particulate inert). The second step is the hydrolysis process of the disintegration products under an enzymatic action to produce sugars, amino acids and long chain fatty acids (LCFA), successively. Then, amino acids and sugars are fermented to produce VFA, hydrogen and carbon dioxide (acidogenesis). Then LCFA, proprionic acid, butyric acid and valeric acid are anaerobically oxided into acetate, carbon dioxide and hydrogen (acetogenesis). Finally, methane can be produced through two paths: the first one is based on acetate whereas the second one is through the reduction of carbon dioxide by molecular hydrogen. The organic species and molecular hydrogen, in this model, are expressed as COD (Chemical Oxygen Demand), whereas inorganic nitrogen and inorganic carbon species are expressed through their

Extensions and modifications were brought to ADM1 to enlarge its prediction capabilities by, taking into account other factors such as, for instance, the sulfato-reductors or the degradation of certain substrates (Wolfsberger and Halubar, 2006) and (Batstone and Keller, 2003). Moreover, Usama Zaher (Usama, 2005) considered the toxic effects of cyanide as an

Concerning simulations of TCOD and SCOD, and TVFA, after estimation of substrate disintegration and hydrolysis parameters, it can be noticed that the simulated results are in

good agreement with the experimental ones as shown on figure 7 and 8 respectively.

**9.1 Application of ADM1 model for simulation of organic solid waste** 

model was able to reproduce the trends of the experimental results.

increase of the loading rate.

temperature of 37°C.

molecular concentrations.

inhibition process for acetate.

the influent is rather more important.


Table 3. Effluent characteristics

Production of Biogas from Sludge Waste and Organic Fraction of Municipal Solid Waste 167

 (simulated TVFA) (measured TVFA)

0 10 20 30 40 50 60 70 80

**Time (days)**

However the simulated results of SCOD are somehow underestimated in comparison with the experimental ones. This may be explained by the fact that the substrate distribution between proteins, carbohydrates and lipids was not measured but default model values

The simulated TVFA results show good digester stability and are in good agreement with

Figure 9 shows variation of the experimental and simulated results of total biogas volume produced, which depends on the nature, the composition and the biodegradability of solids. In this case, mass loading fluctuate as shown by the ORL, it should be underlined that the main objective of these experiments was to increase the ORL to the practical limits in order to treat a maximum quantity of solid waste however it was difficult to maintain it constant. Consequently these variations condition the tendency of biogas volume produced variation. The limitations of ADM1 imply that the simulated biogas production follows an average

Figure 10 shows the experimental and simulated results of biogas production. The biogas is composed principally of methane and carbon dioxide and a small percentage of hydrogen. It can be noticed that the simulated results are in good agreement with the experimental ones. A similar remark concerning the average course of the curve can be held as well. Moreover,

To have a clear picture of what is happening within the system, inorganic carbon (IC) and inorganic nitrogen (IN) as well as pH, were represented on the same graph as presented in

Since pH is approximately equal to 8, IC represents alkalinity. Any variation in alkalinity is due to neutralisation of VFA, if accumulated. Furthermore, alkalinity or IC is more sensitive

course; therefore, the simulated data overlaps partially the experimental values.

they show a good stability in the operating of the reactor

to VFA accumulation than pH and therefore more reliable.

Fig. 8. Comparison between the simulation and the experimental TVFA

0,00

were adopted for this parameter.

the experimental ones as well.

Figure 11.

0,02

0,04

0,06

**Effluent TVFA (Kg COD/m3**

**)**

0,08

0,10

0,12

0,14


Table 4. Characteristics of biogas production


a Middle values obtained from (Mata-Alvarez , 2003)

b Values obtained from (Batstone and Keller, 2003)

Table 5. Initial and estimated values of kinetic parameters

Fig. 7. Comparison between the simulation and the experimental total and souble COD

Biogas volume

GPR

Volume of CH4

Volume of CO2

Kinetic parameter

s

**Kdis Khyd.Ch Khyd.Pr Khyd.Li**

Table 4. Characteristics of biogas production

constant

constant

constant

Disintegration constant Carbohydrate hydrolysis

Proteins hydrolysis

Lipids hydrolysis

Table 5. Initial and estimated values of kinetic parameters

a Middle values obtained from (Mata-Alvarez , 2003) b Values obtained from (Batstone and Keller, 2003)

Effluent TCOD and SCOD (Kg COD/m3

)

Parameters Middle Minimum Maximum Stand. Dev. Num. samp

(m3/day) 0.431 0.153 0.728 0.16 31

(m3/day) 0.3 0.09 0.44 0.10 31

(m3/days) 0.17 0.06 0.28 0.06 31 H2S (ppm) 440 200 1044 204.91 31

> used in ADM1

0.5b 10b 10b 10b

Initial values

0.7 1.25a 0.5a 0.4a

Estimate d values

0.7 1.0 0.7 1.0

Names Units Initial values

Day-1 Day-1 Day-1 Day-1

0 10 20 30 40 50 60 70 80

 (Simulated TCOD) (Simulate SCOD) (measured TCOD) (measured SCOD)

Time (days)

Fig. 7. Comparison between the simulation and the experimental total and souble COD

SGP (m3 biog/kg TVS) 0.51 0.26 1.06 0.16 29

(m3 biogas/m3 day) 0.96 0.34 1.62 0.35 31 % CH4 (%) 60.6 55 65 2.22 40 % CO2 (%) 39.4 35 45 2.22 40

Fig. 8. Comparison between the simulation and the experimental TVFA

However the simulated results of SCOD are somehow underestimated in comparison with the experimental ones. This may be explained by the fact that the substrate distribution between proteins, carbohydrates and lipids was not measured but default model values were adopted for this parameter.

The simulated TVFA results show good digester stability and are in good agreement with the experimental ones as well.

Figure 9 shows variation of the experimental and simulated results of total biogas volume produced, which depends on the nature, the composition and the biodegradability of solids. In this case, mass loading fluctuate as shown by the ORL, it should be underlined that the main objective of these experiments was to increase the ORL to the practical limits in order to treat a maximum quantity of solid waste however it was difficult to maintain it constant. Consequently these variations condition the tendency of biogas volume produced variation. The limitations of ADM1 imply that the simulated biogas production follows an average course; therefore, the simulated data overlaps partially the experimental values.

Figure 10 shows the experimental and simulated results of biogas production. The biogas is composed principally of methane and carbon dioxide and a small percentage of hydrogen. It can be noticed that the simulated results are in good agreement with the experimental ones. A similar remark concerning the average course of the curve can be held as well. Moreover, they show a good stability in the operating of the reactor

To have a clear picture of what is happening within the system, inorganic carbon (IC) and inorganic nitrogen (IN) as well as pH, were represented on the same graph as presented in Figure 11.

Since pH is approximately equal to 8, IC represents alkalinity. Any variation in alkalinity is due to neutralisation of VFA, if accumulated. Furthermore, alkalinity or IC is more sensitive to VFA accumulation than pH and therefore more reliable.

Production of Biogas from Sludge Waste and Organic Fraction of Municipal Solid Waste 169

It is noted that in this study, the simulated results show an acceptable fit for Total chemical oxygene demand (COD), biogas volume and composition, pH and inorganic nitrogen (IN). However, for inorganic carbon (IC), the simulated results do not show a good fit. It was confirmed that IC or bicarbonate alkalinity is a very sensitive parameter to volatile fatty acids (VFA) accumulation, compared to pH variations and hence it can be used as a

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Fig. 9. Comparison between the simulation and the experimental biogas production rate and the variation of the organic loading rate (OLR) with time

Fig. 10. Comparison between the simulation and the experimental % of CO2 and CH4

Fig. 11. Comparison between the simulation and the experimental IC, IN and pH

It is noted that in this study, the simulated results show an acceptable fit for Total chemical oxygene demand (COD), biogas volume and composition, pH and inorganic nitrogen (IN). However, for inorganic carbon (IC), the simulated results do not show a good fit. It was confirmed that IC or bicarbonate alkalinity is a very sensitive parameter to volatile fatty acids (VFA) accumulation, compared to pH variations and hence it can be used as a monitoring parameter.
